Each index \(s\)  corresponds to a point \(\textbf {a}_s\)  in the
semantic vector space defined by the representation layer \(\textbf {q}\) . Since an embedding is optimized for a concept's role in perception and memory,
it implicitly reflects all background that is known about it.
Figure REF  shows an analysis of the entity embeddings, based on the t-SNE visualization [1]}. The plot clearly shows a schema-like organization of concept embeddings in semantic embedding space, also known as a cognitive map [2]}. In cognitive neuroscience, the semantic embedding space is sometimes referred to as conceptual space [3]},
where points denote objects, and regions denote concepts.
<FIGURE>